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M&S Uncertainty Quantification

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-13-C-7401
Agency Tracking Number: B12B-007-0010
Amount: $99,266.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: MDA12-T007
Solicitation Number: 2012.B
Solicitation Year: 2012
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-02-14
Award End Date (Contract End Date): 2013-08-18
Small Business Information
100 North Country Rd.
Setauket, NY 11733-1354
United States
DUNS: 178047015
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (631) 751-4350
Business Contact
Title: President
Phone: (631) 751-4350
Research Institution
 Los Alamos National Laboratory
P.O. Box 1663
Los Alamos, NM 87545-
United States

 (505) 667-3320
 Federally Funded R&D Center (FFRDC)

An emerging consensus in engineering holds that aleatory uncertainty should be propagated by traditional methods of probability theory but that epistemic uncertainty may require methods that do not confuse incertitude with variability by requiring every possibility be associated with a probability that it occurs. Therefore, although Monte Carlo shells that re-run calculations many times while varying input values according to specified distributions are useful, they are insufficient to properly account for epistemic and aleatory uncertainty. Three things are needed to build on the new consensus. The first is a clear and comprehensive roadmap for how various important problems (e.g., arithmetic and logical evaluations, backcalculations, sensitivity analyses, etc.) can be solved under this view. The second is software that enables analysts to automatically propagate through simulations the uncertainty implied by the significant digits of the numbers specifying a model. Such software would require very little training in uncertainty analysis to be useful to analysts. The third need is a software library of recommended methods for common calculations that is usable by modelers and analysts who may not themselves be experts in uncertainty quantification but who recognize the need for and benefits from it.

* Information listed above is at the time of submission. *

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